code: def test_pytorch_wrapper_roundtrip():
      import torch.nn
  
      model = PyTorchWrapper(torch.nn.Linear(2, 3))
      model_bytes = model.to_bytes()
      PyTorchWrapper(torch.nn.Linear(2, 3)).from_bytes(model_bytes)
      with make_tempdir() as path:
          model_path = path / "model"
          model.to_disk(model_path)
          new_model = PyTorchWrapper(torch.nn.Linear(2, 3)).from_bytes(
              model_bytes
          )
          new_model.from_disk(model_path)
  
file_path: thinc/thinc/tests/layers/test_pytorch_wrapper.py
imports: import numpy
  import pytest
  from thinc.api import SGD, ArgsKwargs, CupyOps, Linear, MPSOps, NumpyOps, PyTorchWrapper, PyTorchWrapper_v2, PyTorchWrapper_v3, Relu, chain, get_current_ops, torch2xp, use_ops, xp2torch
  from thinc.backends import context_pools
  from thinc.compat import has_cupy_gpu, has_torch, has_torch_amp, has_torch_mps_gpu
  from thinc.layers.pytorchwrapper import PyTorchWrapper_v3
  from thinc.shims.pytorch import default_deserialize_torch_model, default_serialize_torch_model
  from thinc.shims.pytorch_grad_scaler import PyTorchGradScaler
  from thinc.util import get_torch_default_device
  from ..util import check_input_converters, make_tempdir
label_desc: Use image node_id 6 for calling a global function with example usage: test_pytorch_wrapper_roundtrip() without return types